Brain structure predicts risk for obesity

Early life factors and structural brain network in children with overweight/obesity: The ActiveBrains project

BACKGROUND

The aims of this study were to investigate the association of early life factors, including birth weight, birth length, and breastfeeding practices, with structural brain networks; and to test whether structural brain networks associated with early life factors were also associated with academic performance in children with overweight/obesity (OW/OB).

METHOD

96 children with OW/OB aged 8-11 years (10.03 ± 1.16) from the ActiveBrains project were included. Early life factors were collected from birth records and reported by parents as weight, height, and months of breastfeeding. T1-weighted images were used to identify structural networks using a non-negative matrix factorization (NNMF) approach. Academic performance was evaluated by the Woodcock-Muñoz standardized test battery.

RESULTS

Birth weight and birth length were associated with seven networks involving the cerebellum, cingulate gyrus, occipital pole, and subcortical structures including hippocampus, caudate nucleus, putamen, pallidum, nucleus accumbens, and amygdala. No associations were found for breastfeeding practices. None of the networks linked to birth weight and birth length were linked to academic performance.

CONCLUSIONS

Birth weight and birth length, but not breastfeeding, were associated with brain structural networks in children with OW/OB. Thus, early life factors are related to brain networks, yet a link with academic performance was not observed.

IMPACT

Birth weight and birth length, but not breastfeeding, were associated with several structural brain networks involving the cerebellum, cingulate gyrus, occipital pole, and subcortical structures including hippocampus, caudate, putamen, pallidum, accumbens and amygdala in children with overweight/obesity, playing a role for a normal brain development. Despite no academic consequences, other behavioral consequences should be investigated. Interventions aimed at improving optimal intrauterine growth and development may be of importance to achieve a healthy brain later in life.

Opposite changes in morphometric similarity of medial reward and lateral non-reward orbitofrontal cortex circuits in obesity

Obesity has a profound impact on metabolic health thereby adversely affecting brain structure and function. However, the majority of previous studies used a single structural index to investigate the link between brain structure and body mass index (BMI), which hinders our understanding of structural covariance between regions in obesity. This study aimed to examine the relationship between macroscale cortical organization and BMI using novel morphometric similarity networks (MSNs). The individual MSNs were first constructed from individual eight multimodal cortical morphometric features between brain regions. Then the relationship between BMI and MSNs within the discovery sample of 434 participants was assessed. The key findings were further validated in an independent sample of 192 participants. We observed that the lateral non-reward orbitofrontal cortex (lOFC) exhibited decoupling (i.e., reduction in integration) in obesity, which was mainly manifested by its decoupling with the cognitive systems (i.e., DMN and FPN) while the medial reward orbitofrontal cortex (mOFC) showed de-differentiation (i.e., decrease in distinctiveness) in obesity, which was mainly represented by its de-differentiation with the cognitive and attention systems (i.e., DMN and VAN). Additionally, the lOFC showed de-differentiation with the visual system in obesity, while the mOFC showed decoupling with the visual system and hyper-coupling with the sensory-motor system in obesity. As an important first step in revealing the role of underlying structural covariance in body mass variability, the present study presents a novel mechanism that underlies the reward-control interaction imbalance in obesity, thus can inform future weight-management approaches.

White adipose tissue distribution and amount are associated with increased white matter connectivity

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a deeper characterization of body composition is required, especially considering the links between abdominal obesity and metabolic dysfunction. This study aims to enhance our understanding of the relationship between obesity and WM connectivity by directly assessing the amount and distribution of fat tissue. Whole-body magnetic resonance imaging (MRI) was employed to evaluate total adipose tissue (TAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT), while MR liver spectroscopy measured liver fat content in 63 normal-weight, overweight, and obese males. WM connectivity was quantified using microstructure-informed tractography. Connectome-based predictive modeling was used to predict body composition metrics based on WM connectomes. Our analysis revealed a positive dependency between BMI, TAT, SAT, and WM connectivity in brain regions involved in reward processing and appetite regulation, such as the insula, nucleus accumbens, and orbitofrontal cortex. Increased connectivity was also observed in cognitive control and inhibition networks, including the middle frontal gyrus and anterior cingulate cortex. No significant associations were found between WM connectivity and VAT or liver fat. Our findings suggest that altered neural communication between these brain regions may affect cognitive processes, emotional regulation, and reward perception in individuals with obesity, potentially contributing to weight gain. While our study did not identify a link between WM connectivity and VAT or liver fat, further investigation of the role of various fat depots and metabolic factors in brain networks is required to advance obesity prevention and treatment approaches.

Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD.

Neural structural abnormalities behind altered brain activation in obesity: Evidence from meta-analyses of brain activation and morphometric data

Obesity represents a risk factor for disability with a major bearing on life expectancy. Neuroimaging techniques are contributing to clarify its neurobiological underpinnings. Here, we explored whether structural brain abnormalities might accompany altered brain activations in obesity. We combined and compared data from brain activation studies for food stimuli and the data reported in structural voxel-based morphometry studies. We found that obese individuals have reduced grey matter density and functional activations in the thalamus and midbrain. A functional connectivity analysis based on these two clusters and its quantitative decoding showed that these regions are part of the reward system functional brain network. Moreover, we found specific grey matter hypo-densities in prefrontal cortex for the obese subjects, regions involved in controlled behaviour. These results support theories of obesity that point to reduced bottom-up reward processes (i.e., the Reward Deficit Theory), but also top-down theories postulating a deficit in cognitive control (i.e., the Inhibitory Control Deficit Theory). The same results also warrant a more systematic exploration of obesity whereby the reward of food and the intentional control over consummatory behaviour is manipulated.

Fetal programming of human energy homeostasis brain networks: Issues and considerations

In this paper, we present a transdisciplinary framework and testable hypotheses regarding the process of fetal programming of energy homeostasis brain circuitry. Our model proposes that key aspects of energy homeostasis brain circuitry already are functional by the time of birth (with substantial interindividual variation); that this phenotypic variation at birth is an important determinant of subsequent susceptibility for energy imbalance and childhood obesity risk; and that this brain circuitry exhibits developmental plasticity, in that it is influenced by conditions during intrauterine life, particularly maternal-placental-fetal endocrine, immune/inflammatory, and metabolic processes and their upstream determinants. We review evidence that supports the scientific premise for each element of this formulation, identify future research directions, particularly recent advances that may facilitate a better quantification of the ontogeny of energy homeostasis brain networks, highlight animal and in vitro-based approaches that may better address the determinants of interindividual variation in energy homeostasis brain networks, and discuss the implications of this formulation for the development of strategies targeted towards the primary prevention of childhood obesity.

Gray matter volume alterations in subjects with overweight and obesity: Evidence from a voxel-based meta-analysis

BACKGROUND

Obesity is a multi-systemic disease with complex etiology. And consistent evidence indicated obesity or overweight subjects render brain structure changes. Increasing evidence indicates these subjects have shown widespread structural brain gray matter volume (GMV) changes. However, results from other neuroimaging studies have been inconsistent. Consequently, the question remains whether body mass index (BMI), a gold standard to define obesity/overweight, is associated with brain structural changes.

METHODS

This study will apply an updated meta-analysis of voxel-based GMV studies to compare GMV changes in overweight and obese subjects. Online databases were used to build on relevant studies published before May 2022. The updated Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) explores GMV changes in individuals with overweight and obesity and further examines the correlation between GMV and obesity-related variables, specifically body mass index (BMI).

RESULTS

This research included fourteen studies and provided a whole-brain analysis of GMV distribution in overweight and obese individuals. It revealed lower GMV in brain regions, including the left putamen and right precentral gyrus, in individuals with overweight and obesity compared to lean controls. Further, meta-regression analyses revealed GMV in the left middle occipital gyrus was negatively correlated with the BMI of the whole sample.

CONCLUSION

GMV decreased was reported in reward circuit processing areas and sensorimotor processing areas of individuals with overweight and obesity diagnoses, suggesting an underlying structural basis for reward processing and sensorimotor processing dysregulation in overweight and obese subjects. Our results also suggest that GMV in occipital gyrus, a key region for food visual and gustatory encoding, is negatively associated with BMI. These results provide further evidence for the dysregulated reward circuit in individuals with overweight and obesity.

Obesity and Gray Matter Volume Assessed by Neuroimaging: A Systematic Review

Obesity has become a major public and individual health problem due to its high worldwide prevalence and its relation with comorbid conditions. According to previous studies, obesity is related to an increased risk of cognitive impairment and dementia. This systematic review aims to further examine the present state of the art about the association between obesity and gray matter volume (GMV) as assessed by magnetic resonance imaging (MRI). A search was conducted in Pubmed, SCOPUS and Cochrane of those studies released before 1 February 2021 including MRIs to assess the GMVs in obese participants. From this search, 1420 results were obtained, and 34 publications were finally included. Obesity was mainly measured by the body mass index, although other common types of evaluations were used (e.g., waist circumference, waist-to-hip ratio and plasma leptin levels). The selected neuroimaging analysis methods were voxel-based morphometry (VBM) and cortical thickness (CT), finding 21 and 13 publications, respectively. There were 30 cross-sectional and 2 prospective longitudinal studies, and 2 articles had both cross-sectional and longitudinal designs. Most studies showed a negative association between obesity and GMV. This would have important public health implications, as obesity prevention could avoid a potential risk of GMV reductions, cognitive impairment and dementia.

Female sweet-likers have enhanced cross-modal interoceptive abilities

There are well known phenotypic differences in sweet-liking across individuals, but it remains unknown whether these are related to broader underlying differences in interoceptive abilities (abilities to sense the internal state of the body). Here, healthy women (N = 64) classified as sweet likers (SLs) or sweet dislikers (SDs) completed a bimodal interoception protocol. A heartbeat tracking and a heartbeat discrimination task determined cardiac interoception; both were accompanied by confidence ratings. A water load task, where participants consumed water to satiation and then to maximum fullness was used to assess gastric interoceptive abilities. Motivational state, psychometric characteristics and eating behaviour were also assessed. SLs performed significantly better than SDs on both heartbeat tasks, independently of impulsivity, anxiety, depression, and alexithymia. No differences in metacognitive awareness and subjective interoceptive measures were found. With gastric interoception, SLs were more sensitive to stomach distention, and they ingested less water than SDs to reach satiety when accounting for stomach capacity. SLs also scored higher on mindful and intuitive eating scales and on emotional eating particularly in response to negative stimuli; emotional overeating was fully mediated via interoceptive performance. Overall, our data suggest the SL phenotype may reflect enhanced responsiveness to internal cues more broadly.

Novelty seeking is associated with increased body weight and orbitofrontal grey matter volume reduction

Novelty seeking (NS) has previously been identified as a personality trait that is associated with elevated body mass index (BMI) and obesity. Of note, both obesity and reduced impulse control - a core feature of NS - have previously been associated with grey matter volume (GMV) reductions in the orbitofrontal cortex (OFC). Yet, it remains unknown, if body weight-related grey matter decline in the OFC might be explained by higher levels of NS. To address this question, we studied associations between NS, BMI and brain structure in 355 healthy subjects. Brain images were pre-processed using voxel-based morphometry (VBM). BMI was calculated from self-reported height and weight. The Tridimensional Personality Questionnaire (TPQ) was used to assess NS. NS and BMI were associated positively (r = .137, p = .01) with NS being a significant predictor of BMI (B = 0.172; SE B = 0.05; ß = 0.184; p = 0.001). Significant associations between BMI and GMV specifically in the OFC (x = -44, y = 56, z = -2, t(350) = 4.34, k = 5, p_FWE = 0.011) did not uphold when correcting for NS in the model. In turn, a significant negative association between NS and OFC GMV was found independent of BMI (x = -2, y = 48, z = -10, t(349) = 4.42, k = 88, p_FWE = 0.008). Body mass-related grey matter decrease outside the OFC could not be attributed to NS. Our results suggest that body-weight-related orbitofrontal grey matter reduction can at least partly be linked to higher levels of NS. Given the pivotal role of the OFC in overweight as well as cognitive domains such as impulse inhibition, executive control and reward processing, its association with NS seems to provide a tenable neurobiological correlate for future research.

Familial Obesity Risk and Current Excess Weight Influence Brain Structure in Adolescents

OBJECTIVE

Obesity risk transmits from parents to children. Underlying neural mechanisms were investigated in this study by evaluating influences of familial obesity risk defined by maternal obesity and influences of current overweight on three indices of brain structure in adolescents.

METHODS

In total, 22 lean adolescents with lean mothers (lean low-risk), 25 lean adolescents with mothers with obesity/overweight (lean high-risk), and 36 adolescents with obesity/overweight underwent structural MRI scans for estimation of regional gray and white matter volume and cortical thickness.

RESULTS

The lean high-risk compared with the lean low-risk group demonstrated lower gray and white matter volume and cortical thickness in the postcentral gyrus (somatosensory cortex), lower gray and white matter volume in the opercular cortex (taste cortex), lower gray matter volume and cortical thickness in the anterior cingulate cortex, and lower cortical thickness in the precuneus. Comparisons of the lean and obesity/overweight groups revealed further structural alterations in the postcentral gyrus, posterior cingulate gyrus, and middle temporal gyrus.

CONCLUSIONS

Familial obesity risk and current obesity/overweight were associated with overlapping and distinct patterns of brain structure alterations. Longitudinal studies are warranted to investigate whether structural changes associated with familial obesity risk predict future weight trajectories.

Fronto-limbic white matter fractional anisotropy and body mass index in first-episode schizophrenia spectrum disorder patients compared to healthy controls

In this diffusion tensor imaging study, we explored the associations of body mass index (BMI) with white matter microstructure in first-episode schizophrenia spectrum disorder patients (n = 69) versus healthy controls (n = 93). We focused on fractional anisotropy (FA) measures for fronto-limbic white matter tracts known to connect brain regions which form part of a "core eating network". Secondary objectives included the associations of body mass with global illness severity, psychopathology and depressive symptoms. In a multivariate analysis of covariance (MANCOVA) model, there was a significant interaction between BMI and group (patient versus control) across the fronto-limbic white matter tracts of interest (F(1,155)= 4.91, p = 0.03). In a sub-analysis, BMI was significantly inversely correlated with FA measures for the genu and body of the corpus callosum, left and right tapetum, and left superior fronto-occipital fasciculus in controls. In patients, BMI was significantly positively correlated with white matter FA for the genu of the corpus callosum and left tapetum. Lower BMI was significantly correlated with more severe negative symptoms, as was earlier age of illness onset. Body mass may be differentially associated with fronto-limbic white matter microstructure in first-episode schizophrenia spectrum disorder compared to controls.

Obesity is associated with reduced orbitofrontal cortex volume: A coordinate-based meta-analysis

Neural models of obesity vary in their focus upon prefrontal and striatal differences. Animal and human studies suggest that differential functioning of the orbitofrontal cortex is associated with obesity. However, meta-analyses of functional neuroimaging studies have not found a clear relationship between the orbitofrontal cortex and obesity. Meta-analyses of structural imaging studies of obesity have shown mixed findings with regards to an association with reduced orbitofrontal cortex gray matter volume. To clarify these findings, we conducted a meta-analysis of 25 voxel-based morphometry studies, and found that greater body mass index is associated with decreased gray matter volume in the right orbitofrontal cortex (Brodmanns' areas 10 and 11), where family-wise corrected p < .05, N = 7,612. Use of the right orbitofrontal cortex as a seed in a Neurosynth Network Coactivation analysis showed that this region is associated with activity in the left frontal medial cortex, left temporal lobe, right precuneus cortex, posterior division of the left middle temporal gyrus, and right frontal pole. When Neurosynth Network Coactivation results were submitted as regions of interest in the Human Connectome Project data, we found that greater body mass index was associated with greater activity in left frontal medial cortex response to the Gambling Task, where p < .05, although this did not survive Bonferroni-correction. Our findings highlight the importance of the orbitofrontal cortex structure and functioning in neural models of obesity. Exploratory analyses suggest more studies are needed that examine the functional significance of reduced orbitofrontal cortex gray matter volume in obesity, and the effect of age and weight changes on this relationship using longitudinal designs.

Neurovegetative symptom subtypes in young people with major depressive disorder and their structural brain correlates

Depression is a leading cause of burden of disease among young people. Current treatments are not uniformly effective, in part due to the heterogeneous nature of major depressive disorder (MDD). Refining MDD into more homogeneous subtypes is an important step towards identifying underlying pathophysiological mechanisms and improving treatment of young people. In adults, symptom-based subtypes of depression identified using data-driven methods mainly differed in patterns of neurovegetative symptoms (sleep and appetite/weight). These subtypes have been associated with differential biological mechanisms, including immuno-metabolic markers, genetics and brain alterations (mainly in the ventral striatum, medial orbitofrontal cortex, insular cortex, anterior cingulate cortex amygdala and hippocampus). K-means clustering was applied to individual depressive symptoms from the Quick Inventory of Depressive Symptoms (QIDS) in 275 young people (15-25 years old) with MDD to identify symptom-based subtypes, and in 244 young people from an independent dataset (a subsample of the STAR*D dataset). Cortical surface area and thickness and subcortical volume were compared between the subtypes and 100 healthy controls using structural MRI. Three subtypes were identified in the discovery dataset and replicated in the independent dataset; severe depression with increased appetite, severe depression with decreased appetite and severe insomnia, and moderate depression. The severe increased appetite subtype showed lower surface area in the anterior insula compared to both healthy controls. Our findings in young people replicate the previously identified symptom-based depression subtypes in adults. The structural alterations of the anterior insular cortex add to the existing evidence of different pathophysiological mechanisms involved in this subtype.

Brain structures associated with eating behaviors in normal-weight young females

Eating behaviors play an important role in individuals' development, and restrained eaters have a higher risk of obesity in the future. In the present study, we used the Three-Factor Eating Questionnaire to measure restrained eating, uncontrolled eating, and emotional eating in 158 young, normal-weight, Chinese women. We developed a multiple linear regression model to identify significant structural brain changes associated with the above-mentioned eating behaviors. Uncontrolled eating scores were positively associated with the gray matter volume (GMV) of the cerebellum, and negatively associated with the GMV on the left side of the anterior cingulate cortex, middle cingulate cortex, and supplementary motor areas, indicating that uncontrolled eating behaviors not only are less inhibitory but also appear to be associated with the low-level processing of appetite. Increased GMV on the right side of the precuneus was associated with a higher level of restrained eating, which might be thus related to a lower sensitivity to behavioral inhibition in young females who follow a diet. In addition, we did not find a relationship between emotional eating behavior and GMV. Our findings show that eating-behavior-related structural brain changes may lead to a decrease in inhibition and an increase in food sensitivity.

Adiposity is related to cerebrovascular and brain volumetry outcomes in the RUN DMC study

OBJECTIVE

Adiposity predictors, body mass index (BMI), waist circumference (WC), and blood leptin and total adiponectin levels were associated with components of cerebral small vessel disease (CSVD) and brain volumetry in 503 adults with CSVD who were ≥50 years of age and enrolled in the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort (RUN DMC).

METHODS

RUN DMC participants were followed up for 9 years (2006-2015). BMI, WC, brain imaging, and dementia diagnoses were evaluated at baseline and follow-up. Adipokines were measured at baseline. Brain imaging outcomes included CSVD components, white matter hyperintensities, lacunes, microbleeds, gray and white matter, hippocampal, total brain, and intracranial volumes.

RESULTS

Cross-sectionally among men at baseline, higher BMI, WC, and leptin were associated with lower gray matter and total brain volumes, and higher BMI and WC were associated with lower hippocampal volume. At follow-up 9 years later, higher BMI was cross-sectionally associated with lower gray matter volume, and an obese WC (>102 cm) was protective for ≥1 lacune or ≥1 microbleed in men. In women, increasing BMI and overweight or obesity (BMI ≥25 kg/m² or WC >88 cm) were associated with ≥1 lacune. Longitudinally, over 9 years, a baseline obese WC was associated with decreasing hippocampal volume, particularly in men, and increasing white matter hyperintensity volume in women and men.

CONCLUSIONS

Anthropometric and metabolic adiposity predictors were differentially associated with CSVD components and brain volumetry outcomes by sex. Higher adiposity is associated with a vascular-neurodegenerative spectrum among adults at risk for vascular forms of cognitive impairment and dementias.

Pituitary Gland Functional Connectivity and BMI

The pituitary gland (PG) influences body weight through hormonal releases; however, the relation between body weight and PG’s co-activities with other brain regions remains unclear. Here, we aimed to identify (1) the functional connectivity of the PG and (2) PG functional connectivity associated with body mass index by examining resting state functional magnetic resonance imaging data. Using enhanced Nathan Kline Institute-Rockland Sample, PG functional connectivity of 494 individuals was analyzed to assess in voxel-wise fashion. A negative association was found between BMI and PG functional connectivity with the orbitofrontal cortex, hippocampus, putamen, and temporal lobe. Our results show PG dysconnectivity to these regions is associated with higher BMI and implicate that the connectivity between these dopaminergic regions and PG may be associated with body weight maintenance through feeding behavior and growth.

Bariatric Surgery Induces White and Grey Matter Density Recovery in the Morbidly Obese: A Voxel-Based Morphometric Study

Obesity is associated with lowered brain's grey (GM) and white matter (WM) density as measured by voxel-based morphometry (VBM). Nevertheless, it remains unknown whether obesity has a causal influence on cerebral atrophy. We recruited 47 morbidly obese subjects (mean BMI = 42.2, SD = 4.0, 42 females and five males) eligible for bariatric surgery and 29 non-obese subjects (mean BMI = 23.2, SD = 2.8, 23 females and six males) served as controls. Baseline scans were acquired with T1-weighted magnetic resonance imaging (MRI) at 1.5 Tesla; obese participants were scanned again six months after the surgery. Local GM and WM densities were quantified using VBM. Full-volume analyses were used for comparing baseline between-group differences as well as the effects of surgery-induced weight loss in the morbidly obese. Metabolic variables were used in linear models to predict WM and GM densities. Obese subjects had initially lower GM densities in widespread cortical areas including frontal, parietal, and temporal regions as well as insulae. Lower WM densities were observed throughout the WM. Bariatric surgery and concomitant weight loss resulted in global increase in WM density. Grey matter increase was limited to occipital and inferior temporal regions. Metabolic variables were associated with brain densities. We conclude that weight loss results in global recovery of WM as well as local recovery of grey matter densities. These changes likely reflect improved brain tissue integrity. Hum Brain Mapp 37:3745-3756, 2016. © 2016 Wiley Periodicals, Inc.

Decision Making Deficits in Relation to Food Cues Influence Obesity: A Triadic Neural Model of Problematic Eating

In this review article we propose a model of the brain systems, the deficiency of which may underlie problematic eating. This integrative model is based on studies that have focused on discrete brain components involved in problematic eating, combined with insights from studies on the neurocognitive basis of other addictive and problematic behaviors. The model includes: (a) a hyper-functioning reward anticipation and processing system (amygdala-striatum dependent) in response to food-related cues; (b) a hypo-functioning reflective and inhibitory control system (prefrontal cortex dependent), that fails to anticipate and properly weigh future outcomes; and (c) an altered interoceptive awareness system (insular cortex dependent) that translates homeostatic violation signals into a strong consumption desire that hijacks the inhibitory system and excites the reward system. We posit that when the abovementioned systems are imbalanced in such a way that the dopamine axis is hyperactive in relation to food cues and the inhibitory system is weak, and this is further aggravated by an altered interoceptive awareness system, people may experience loss of control or inability to resist tempting/rewarding foods. This loss of control over food consumption can explain, at least in part, the development of excess weight and contribute to the obesity epidemic.

Microstructural abnormalities in white and gray matter in obese adolescents with and without type 2 diabetes

Aims/hypotheses

In adults, type 2 diabetes and obesity have been associated with structural brain changes, even in the absence of dementia. Some evidence suggested similar changes in adolescents with type 2 diabetes but comparisons with a non-obese control group have been lacking. The aim of the current study was to examine differences in microstructure of gray and white matter between adolescents with type 2 diabetes, obese adolescents and healthy weight adolescents.

Methods

Magnetic resonance imaging data were collected from 15 adolescents with type 2 diabetes, 21 obese adolescents and 22 healthy weight controls. Volumetric differences in the gray matter between the three groups were examined using voxel based morphology, while tract based spatial statistics was used to examine differences in the microstructure of the white matter.

Results

Adolescents with type 2 diabetes and obese adolescents had reduced gray matter volume in the right hippocampus, left putamen and caudate, bilateral amygdala and left thalamus compared to healthy weight controls. Type 2 diabetes was also associated with significant regional changes in fractional anisotropy within the corpus callosum, fornix, left inferior fronto-occipital fasciculus, left uncinate, left internal and external capsule. Fractional anisotropy reductions within these tracts were explained by increased radial diffusivity, which may suggest demyelination of white matter tracts. Mean diffusivity and axial diffusivity did not differ between the groups.

Conclusion/interpretation

Our data shows that adolescent obesity alone results in reduced gray matter volume and that adolescent type 2 diabetes is associated with both white and gray matter abnormalities.

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Type 2 diabetes and obesity in adolescents is associated with reduced gray matter volume.

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Type 2 diabetes was associated with significant regional changes in FA.

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FA reductions within these tracts were explained by increased RD.

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Mean diffusivity and axial diffusivity did not differ between the groups.

Newborn insula gray matter volume is prospectively associated with early life adiposity gain

Background

The importance of energy homeostasis brain circuitry in the context of obesity is well established, however, the developmental ontogeny of this circuitry in humans is currently unknown. Here, we investigate the prospective association between newborn gray matter (GM) volume in the insula, a key brain region underlying energy homeostasis, and change in percent body fat accrual over the first six months of postnatal life, an outcome that represents among the most reliable infant predictors of childhood obesity risk.

Methods

52 infants (29 male, 23 female, gestational age at birth=39[1.5] weeks) were assessed using structural MRI shortly after birth (postnatal age at MRI scan=25.9[12.2] days), and serial Dual X-Ray Absorptiometry shortly after birth (postnatal age at DXA scan 1=24.6[11.4] days) and at six months of age (postnatal age at DXA scan 2=26.7[3.3] weeks).

Results

Insula GM volume was inversely associated with change in percent body fat from birth to six-months postnatal age and accounted for 19% of its variance (β=-3.6%/S.D., p=0.001). This association was driven by the central-posterior portion of the insula, a region of particular importance for gustation and interoception. The direction of this effect is in concordance with observations in adults, and the results remained statistically significant after adjusting for relevant covariates and potential confounding variables.

Conclusions

Together, these findings suggest an underlying neural basis of childhood obesity that precedes the influence of the postnatal environment. The identification of plausible brain-related biomarkers of childhood obesity risk that predate the influence of the postnatal obesogenic environment may contribute to an improved understanding of propensity for obesity, early identification of at-risk individuals, and intervention targets for primary prevention.

Regional Gray Matter Volume Is Associated with Restrained Eating in Healthy Chinese Young Adults: Evidence from Voxel-Based Morphometry

Highlight

Participants were non-clinical young adults with different restrained eating levels.

We assessed relations of restrained eating (RE) with regional gray matter volume (rGMV).

High RE scores were related to larger GMV in specific areas related to reward.

High RE scores were also linked to less GMV in regions related to response inhibition.

Objective: Dieting is a popular method of weight control. However, few dieters are able to maintain initial weight losses over an extended period of time. Why do most restrained dieters fail to lose weight? Alterations in brain structures associated with restrained eating (RE) represent one potentially important mechanism that contributes to difficulties in maintaining weight loss within this group. To evaluate this contention, we investigated associations between intentional, sustained restriction of food intake to lose or maintain body weight, and regional gray matter volume (rGMV) within a large non-clinical young adult, sample.

Methods: Participants (150 women, 108 men) completed measures of RE and demographics prior to undergoing an MRI scan. Voxel-based morphometry (VBM) evaluated strengths of association between RE scores and rGMV.

Results: Higher RE levels corresponded to more rGMV in regions linked to risk of overeating and binge-eating including the left insula and orbitofrontal cortex (OFC). Conversely, RE had significant negative correlations with rGMV in the left and right posterior cingulum gyrus, regions linked to inhibitory control and potential risk for future weight gain.

Conclusions: Together, findings suggested individual differences in RE among young adults correspond to GMV variability in regions linked to overweight and obesity risk.

Obesity and insulin resistance are associated with reduced activity in core memory regions of the brain

Increasing research in animals and humans suggests that obesity may be associated with learning and memory deficits, and in particular with reductions in episodic memory. Rodent models have implicated the hippocampus in obesity-related memory impairments, but the neural mechanisms underlying episodic memory deficits in obese humans remain undetermined. In the present study, lean and obese human participants were scanned using fMRI while completing a What-Where-When episodic memory test (the “Treasure-Hunt Task”) that assessed the ability to remember integrated item, spatial, and temporal details of previously encoded complex events. In lean participants, the Treasure-Hunt task elicited significant activity in regions of the brain known to be important for recollecting episodic memories, such as the hippocampus, angular gyrus, and dorsolateral prefrontal cortex. Both obesity and insulin resistance were associated with significantly reduced functional activity throughout the core recollection network. These findings indicate that obesity is associated with reduced functional activity in core brain areas supporting episodic memory and that insulin resistance may be a key player in this association.

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Obesity associated with reduced activity in core recollection network during episodic memory.

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Insulin resistance associated with reduced activity in core recollection network during episodic memory.

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Insulin resistance, but not obesity, associated with poorer memory performance.

The obese brain as a heritable phenotype: a combined morphometry and twin study

Background

Body weight and adiposity are heritable traits. To date it remains unknown whether obesity-associated brain structural alterations are under a similar level of genetic control.

Methods

For this study we utilized magnetic resonance imaging (MRI) data from the Human Connectome Project. Voxel based morphometry (VBM) was used to investigate associations between body mass index (BMI) and regional gray matter volume (GMV) in a sample of 875 young adults with a wide BMI range (386m/489f; age 28.8 ± 3.7y; BMI 26.6 ± 5.3 kg*m-2), that included 86 pairs of monozygotic twins and 82 pairs of dizygotic twins. Twin data were analyzed by applying the additive genetic, common environmental and residual effects (ACE) model to determine heritability of brain regions that were associated with BMI.

Results

We observed positive associations between BMI and GMV in the ventromedial prefrontal cortex and the right cerebellum and widespread negative associations within the prefrontal cortex, cerebellum, temporal lobes and distinct subcortical structures. Varying degrees of heritability were found for BMI-associated brain regions, with highest heritability estimates for cerebellar GMV and subcortical structures.

Conclusions

These data indicate that brain regions associated with obesity are subject to differing levels of genetic control and environmental influences. Specific brain regions with high heritability might represent an inherent vulnerability factor for obesity.

Baseline gray- and white-matter volume predict successful weight loss in the elderly

OBJECTIVE

The purpose of this study was to investigate whether structural brain phenotypes could be used to predict weight loss success following behavioral interventions in older adults with overweight or obesity and cardiometabolic dysfunction.

METHODS

A support vector machine with a repeated random subsampling validation approach was used to classify participants into the upper and lower halves of the weight loss distribution following 18 months of a weight loss intervention. Predictions were based on baseline brain gray matter and white matter volume from 52 individuals who completed the intervention and a magnetic resonance imaging session.

RESULTS

The support vector machine resulted in an average classification accuracy of 72.62% based on gray matter and white matter volume. A receiver operating characteristic analysis indicated that classification performance was robust based on an area under the curve of 0.82.

CONCLUSIONS

Findings suggest that baseline brain structure was able to predict weight loss success following 18 months of treatment. The identification of brain structure as a predictor of successful weight loss was an innovative approach to identifying phenotypes for responsiveness to intensive lifestyle interventions. This phenotype could prove useful in future research focusing on the tailoring of treatment for weight loss.

Higher Adolescent Body Mass Index Is Associated with Lower Regional Gray and White Matter Volumes and Lower Levels of Positive Emotionality

Adolescent obesity is associated with an increased chance of developing serious health risks later in life. Identifying the neurobiological and personality factors related to increases in adiposity is important to understanding what drives maladaptive consummatory and exercise behaviors that result in obesity. Previous research has largely focused on adults with few findings published on interactions among adiposity, brain structure, and personality. In this study, Voxel Based Morphometry (VBM) was used to identify associations between gray and white matter volumes and increasing adiposity, as measured by Body Mass Index percentile (BMI%), in 137 adolescents (age range: 9–20 years, BMI% range: 5.16–99.56). Variations in gray and white matter volume and BMI% were then linked to individual differences in personality measures from the Multidimensional Personality Questionnaire (MPQ). After controlling for age and other covariates, BMI% correlated negatively with gray matter volume in the bilateral caudate (right: partial r = −0.338, left: r = −0.404), medial prefrontal cortex (partial r = −0.339), anterior cingulate (partial r = −0.312), bilateral frontal pole (right: partial r = −0.368, left: r = −0.316), and uncus (partial r = −0.475) as well as white matter volume bilaterally in the anterior limb of the internal capsule (right: partial r = −0.34, left: r = −0.386), extending to the left middle frontal subgyral white matter. Agentic Positive Emotionality (PEM-AG) was correlated negatively with BMI% (partial r = −0.384). PEM-AG was correlated positively with gray matter volume in the right uncus (partial r = 0.329). These results suggest that higher levels of adiposity in adolescents are associated with lower trait levels in reward-related personality domains, as well as structural variations in brain regions associated with reward processing, control, and sensory integration.

Gray matter alterations and correlation of nutritional intake with the gray matter volume in prediabetes

The neurophysiology of prediabetes plays an important role in preventive medicine. The dysregulation of glucose metabolism is likely linked to changes in neuron-related gray matter. Therefore, we designed this study to investigate gray matter alterations in medication-naive prediabetic patients. We expected to find alterations in the gray matter of prediabetic patients.A total of 64 prediabetic patients and 54 controls were enrolled. All subjects received T1 scans using a 3-T magnetic resonance imaging machine. Subjects also completed nutritional intake records at the 24-hour and 3-day time points to determine their carbohydrate, protein, fat, and total calorie intake. We utilized optimized voxel-based morphometry to estimate the gray matter differences between the patients and controls. In addition, the preprandial serum glucose level and the carbohydrate, protein, fat, and total calorie intake levels were tested to determine whether these parameters were correlated with the gray matter volume.Prediabetic patients had lower gray matter volumes than controls in the right anterior cingulate gyrus, right posterior cingulate gyrus, left insula, left super temporal gyrus, and left middle temporal gyrus (corrected P < 0.05; voxel threshold: 33). Gray matter volume in the right anterior cingulate was also negatively correlated with the preprandial serum glucose level gyrus in a voxel-dependent manner (r = -0.501; 2-tailed P = 0.001).The cingulo-temporal and insula gray matter alterations may be associated with the glucose dysregulation in prediabetic patients.

Eating behavior associated with gray matter volume alternations: A voxel based morphometry study

Little is known about whether eating behavior is associated with alterations of brain structure or whether the possible alterations are related to body weight status. The current study employed structural imaging from an open MRI data set (http://fcon_1000.

PROJECTS

nitrc.org/indi/pro/nki.html) to examine the relationship between eating behavior traits and brain structural changes. The eating behavior traits were measured by the Three Factor Eating Questionnaire Scale. The brain structural alterations were analyzed using the Voxel Based Morphometry (VBM) method, and a multiple linear regression model was constructed to identify significant brain structural changes that related to eating behavior factors. We found that cognitive restraint of eating was positively correlated with the gray matter volume (GMV) in the dorsolateral prefrontal cortex (DLPFC) and negatively correlated with the GMV in the putamen; disinhibition scores were negatively associated with the GMV in the left middle frontal gyrus; hunger scores showed a positive correlation with the GMV in the hypothalamus and the visual memory areas and a negative association with the GMV in the inferior temporal gyrus and the bilateral middle frontal gyrus. These results indicated a close connection between the eating behavior traits and structural changes in particular brain regions. Conjunction analysis was also performed to further explore the brain structural alterations that were commonly associated with eating behavior and weight status. The findings add to our understanding of the neural basis underlying eating behaviors, and the connection between these behaviors and body weight status.

Association between waist circumference and gray matter volume in 2344 individuals from two adult community-based samples

We analyzed the putative association between abdominal obesity (measured in waist circumference) and gray matter volume (Study of Health in Pomerania: SHIP-2, N=758) adjusted for age and gender by applying volumetric analysis and voxel-based morphometry (VBM) with VBM8 to brain magnetic resonance (MR) imaging. We sought replication in a second, independent population sample (SHIP-TREND, N=1586). In a combined analysis (SHIP-2 and SHIP-TREND) we investigated the impact of hypertension, type II diabetes and blood lipids on the association between waist circumference and gray matter. Volumetric analysis revealed a significant inverse association between waist circumference and gray matter volume. VBM in SHIP-2 indicated distinct inverse associations in the following structures for both hemispheres: frontal lobe, temporal lobes, pre- and postcentral gyrus, supplementary motor area, supramarginal gyrus, insula, cingulate gyrus, caudate nucleus, olfactory sulcus, para-/hippocampus, gyrus rectus, amygdala, globus pallidus, putamen, cerebellum, fusiform and lingual gyrus, (pre-) cuneus and thalamus. These areas were replicated in SHIP-TREND. More than 76% of the voxels with significant gray matter volume reduction in SHIP-2 were also distinct in TREND. These brain areas are involved in cognition, attention to interoceptive signals as satiety or reward and control food intake. Due to our cross-sectional design we cannot clarify the causal direction of the association. However, previous studies described an association between subjects with higher waist circumference and future cognitive decline suggesting a progressive brain alteration in obese subjects. Pathomechanisms may involve chronic inflammation, increased oxidative stress or cellular autophagy associated with obesity.

Multi-level block permutation

Under weak and reasonable assumptions, mainly that data are exchangeable under the null hypothesis, permutation tests can provide exact control of false positives and allow the use of various non-standard statistics. There are, however, various common examples in which global exchangeability can be violated, including paired tests, tests that involve repeated measurements, tests in which subjects are relatives (members of pedigrees) - any dataset with known dependence among observations. In these cases, some permutations, if performed, would create data that would not possess the original dependence structure, and thus, should not be used to construct the reference (null) distribution. To allow permutation inference in such cases, we test the null hypothesis using only a subset of all otherwise possible permutations, i.e., using only the rearrangements of the data that respect exchangeability, thus retaining the original joint distribution unaltered. In a previous study, we defined exchangeability for blocks of data, as opposed to each datum individually, then allowing permutations to happen within block, or the blocks as a whole to be permuted. Here we extend that notion to allow blocks to be nested, in a hierarchical, multi-level definition. We do not explicitly model the degree of dependence between observations, only the lack of independence; the dependence is implicitly accounted for by the hierarchy and by the permutation scheme. The strategy is compatible with heteroscedasticity and variance groups, and can be used with permutations, sign flippings, or both combined. We evaluate the method for various dependence structures, apply it to real data from the Human Connectome Project (HCP) as an example application, show that false positives can be avoided in such cases, and provide a software implementation of the proposed approach.

Compromised white matter integrity in obesity

Obesity is associated with both structural and functional changes of the central nervous system. While gray matter alterations in obesity point to a consistent reduction with increasing body mass index (BMI), volumetric changes in white matter are more complex and less conclusive. Hence, more recently, diffusion tensor imaging (DTI) has been employed as a highly sensitive tool to investigate microstructural changes in white matter structure. Parameters of diffusivity and anisotropy are used to evaluate white matter and fibre integrity as well as axonal and myelin degeneration. Fractional anisotropy (FA) is the most commonly used parameter as it is the best estimate of fibre integrity. The focus of this review was on the relationship between obesity and brain alterations assessed by DTI. Altogether, these studies have shown a loss of white matter integrity with obesity-related factors, especially in tracts within the limbic system and those connecting the temporal and frontal lobe. More specifically, multiple studies found an inverse association between BMI and FA in the corpus callosum, fornix, cingulum and corona radiata in elderly and young adults as well as children. Furthermore, significant interactions were observed between BMI and age, pointing to accelerated ageing of white matter structure in obese.

Does the brain shrink as the waist expands?

Recent studies suggest that being overweight or obese is related to worse cognitive performance, particularly executive function. Obesity may also increase the risk of Alzheimer's disease. Consequently, there has been increasing interest in whether adiposity is related to gray or white matter (GM, WM) atrophy. In this review, we identified and critically evaluated studies assessing obesity and GM or WM volumes either globally or in specific regions of interest (ROIs). Across all ages, higher adiposity was consistently associated with frontal GM atrophy, particularly in prefrontal cortex. In children and adults <40 years of age, most studies found no relationship between adiposity and occipital or parietal GM volumes, whereas findings for temporal lobe were mixed. In middle-aged and aged adults, a majority of studies found that higher adiposity is associated with parietal and temporal GM atrophy, whereas results for precuneus, posterior cingulate, and hippocampus were mixed. Higher adiposity had no clear association with global or regional WM in any age group. We conclude that higher adiposity may be associated with frontal GM atrophy across all ages and parietal and temporal GM atrophy in middle and old age.

Propensity to obesity impacts the neuronal response to energy imbalance

The mechanisms responsible for the propensity to gain weight or remain normal weight are poorly understood. The objective of this study was to study the neuronal response to visual food cues during short-term energy imbalance in healthy adults recruited as obesity-resistant (OR) or obesity-prone (OP) based on self-identification, body mass index, and personal/family weight history. Twenty-five OR and 28 OP subjects were studied in underfed (UF) and overfed (OF) as compared to eucaloric (EU) conditions in a randomized crossover design. Each study phase included a 3-day run-in diet, 1 day of controlled feeding (basal energy needs for EU, 40% above/below basal energy needs for OF/UF), and a test day. On the test day, fMRI was performed in the acute fed stated (30 min after a test meal) while subjects viewed images of foods of high hedonic value and neutral non-food objects. Measures of appetite and hormones were also performed before and every 30 min after the test meal. UF was associated with significantly increased activation of insula, somatosensory cortex, inferior and medial prefrontal cortex (PFC), parahippocampus, precuneus, cingulate, and visual cortex in OR. However, UF had no impact in OP. As a result, UF was associated with significantly greater activation, specifically in the insula, inferior PFC, and somatosensory cortex in OR as compared to OP. While OF was overall associated with reduced activation of inferior visual cortex, no group interaction was observed with OF. In summary, these findings suggest that individuals resistant to weight gain and obesity are more sensitive to short-term energy imbalance, particularly with UF, than those prone to weight gain. The inability to sense or adapt to changes in energy balance may represent an important mechanism contributing to excess energy intake and risk for obesity.

The effects of energy balance, obesity-proneness and sex on the neuronal response to sweet taste

We have previously shown that propensity for weight gain, energy balance state and sex are important determinants of the neuronal response to visual food cues. It is not clear, though, whether these factors also impact the neuronal response to taste. The objective of this study was to examine the neuronal response to sweet taste during energy imbalance in men and women recruited to be obesity-prone (OP) or obesity-resistant (OR). OP (13 men and 12 women) and OR (12 men and 12 women) subjects were studied after 1 day of eucaloric, overfed and underfed conditions in a randomized crossover design. On each test day, fMRI was performed in the respective acute fed state while subjects received in random order 60 trials each of 1M sucrose solution (SU), or artificial saliva (AS) following a visual cue predicting the taste. The neuronal response to SU versus AS expectation was significantly greater in the amygdala, orbitofrontal cortex, putamen and insula in OR versus OP; SU receipt was not different between groups. There were also sex-based differences with men having greater neuronal response to SU versus AS receipt in the caudate than women. The results, however, were not impacted by the state of energy balance. In summary, response to expectation but not receipt of basic sweet taste was different in OR compared to OP, highlighting the importance of learning and conditioning in the propensity to gain weight. Response to sucrose taste receipt was stronger in men than women, raising questions about the effect of sex hormones on brain response to food.

Mitochondrial dysfunction and oxidative damage in the brain of diet-induced obese rats but not in diet-resistant rats

AIMS

It has been suggested that obesity triggered by consuming a high-fat diet (HF) can account for oxidative damage and mitochondrial dysfunction. Thus, we aim to explore the oxidative stress and mitochondrial dysfunction detected in the brain of diet-induced obese (DIO) rats.

MAIN METHODS

Sprague-Dawley (SD) rats were fed either a HF diet or a normal-fat (NF) diet for 10weeks to obtain the control (CON), DIO and diet-resistant (DR) rats. d-Galactose was injected subcutaneously for 10weeks to establish oxidative stress model (MOD) rats. Then, the levels of total antioxidant capacity (T-AOC), lipid peroxidation (LPO), malondialdehyde (MDA), both in plasma and brain tissue, and catalase (CAT) in plasma were measured using enzymic assay kits and the levels of ghrelin, neuropeptide Y (NPY) and leptin in both plasma and brain tissue were measured by using enzyme-linked immunosorbent assay (ELISA) kits. Mitochondrial reactive oxygen species (ROS) formation in brain tissues was detected with 2, 7-dichlorofluorescein diacetate (DCFH2-DA) dyeing. The mitochondrial membrane potential (MMP) was measured with tetrachloro-tetraethyl benzimidazol carbocyanine iodide (JC-1) by a flow cytometer.

KEY FINDINGS

HF diet leads to an obese or DR state characterized by increased or decreased adiposity. The HF diet increased brain LPO, which was accompanied by lower ghrelin levels in DIO rats compared with DR rats. In addition, the increased mitochondrial ROS and lower MMP were detected in DIO rat comparing with DR rats.

SIGNIFICANCE

The current results demonstrated that mitochondrial dysfunction and oxidative damage in the brains of DIO rats, induced by HF diets, might be measurable.

Optogenetic and chemogenetic insights into the food addiction hypothesis

Obesity is clinically diagnosed by a simple formula based on the weight and height of a person (body mass index), but is associated with a host of other behavioral symptoms that are likely neurological in origin. In recent years, many scientists have asked whether similar behavioral and cognitive changes occur in drug addiction and obesity, lending many to discuss the potential for “food addiction”. Advances in understanding the circuitry underlying both feeding behaviors and drug addiction may allow us to consider this question from the viewpoint of neural circuits, to complement behavioral perspectives. Here, we review advances in understanding of these circuits and use them to consider whether drawing comparisons to drug addiction is helpful for understanding certain forms of obesity.

Brain region-specific changes in N-acylethanolamine contents with time of day

The N-acylethanolamines (NAEs) exert important behavioral, physiological, and immunological effects through actions at cannabinoid and other receptors. We measured concentrations of three NAEs, the Km and Vmax for fatty acid amide hydrolysis (FAAH), FAAH protein and FAAH mRNA in prefrontal cortex, hippocampus, hypothalamus, amygdala, striatum, and cerebellum at 4 h intervals, starting at 03:00. Significant differences in N-arachidonylethanolamine contents among the times examined occur in the prefrontal cortex (PFC), hippocampus, hypothalamus, and striatum. N-Oleoylethanolamine concentrations exhibit large fluctuations over the day in the cerebellum, including a threefold decrease between 19:00 and 23:00. N-Palmitoylethanolamine and N-oleoylethanolamine were significantly, positively correlated in all regions examined except the hypothalamus. FAAH Km values are significantly affected by time of day in PFC, hippocampus and amygdala and FAAH Vmax values are significantly affected in PFC, hippocampus and cerebellum. However, correlational data indicate that FAAH does not play a primary role in the circadian regulation of the NAE concentrations. FAAH protein expression is not significantly different among the harvest times in any brain region examined. Concentrations of 2-arachidonoylglycerol are significantly affected by time of harvest in the striatum and cerebellum, but not in other brain regions. Together, these data indicate that the NAEs exhibit diverse patterns of change with time of day that are likely the result of alterations in biosynthesis, and support the hypothesis that N-arachidonylethanolamine is a tonic activator of cannabinoid receptor signaling.

Appetitive traits from infancy to adolescence: using behavioral and neural measures to investigate obesity risk

We come into the world with enduring predispositions towards food, which interact with environmental factors to influence our eating behaviors and weight trajectories. But our fates are not sealed - by learning more about this process we can identify ways to intervene. To advance this goal this we need to be able to assess appetitive traits such as food cue responsiveness and satiety sensitivity at different developmental stages. Assessment methods might include behavioral measures (e.g. eating behavior tests, psychometric questionnaires), but also biomarkers such as brain responses to food cues measured using fMRI. Evidence from infants, children and adolescents suggests that these indices of appetite differ not only with body weight, but also with familial obesity risk as assessed by parent weight, which reflects both genetic and environmental influences, and may provide a useful predictor of obesity development. Behavioral and neural approaches have great potential to inform each other: examining eating behavior can help us identify meaningful appetitive endophenotypes whose neural bases can be probed, while increasing knowledge of the shared neurobiology underlying appetite, obesity, and related behaviors and disorders may ultimately lead to innovative generalized interventions. Another challenge will be to combine comprehensive behavioral and neural assessments of appetitive traits with measures of relevant genetic and environmental factors within long-term prospective studies. This approach may help to identify the biobehavioral precursors of obesity, and lay the foundations for targeted neurobehavioral interventions that can interrupt the pathway to excess weight.

Eating-related behaviors and appetite during energy imbalance in obese-prone and obese-resistant individuals

While the majority of Americans are now overweight, some individuals maintain their weight with minimal effort. This study investigated behavioral differences between 58 individuals recruited as either obese-resistant (OR) or obese-prone (OP) based on self-identification, BMI, and personal/family weight history. Subjects were studied during Eucaloric (EU), Overfed (OF), and Underfed (UF) phases which included a run-in diet, 1 day intervention diet, and a study day. At baseline, subjects completed the Three Factor Eating Questionnaire (TFEQ) and Power of Food Scale (PFS). On the study day, ratings of appetite, food appeal and desire, and food cravings were performed in response to a breakfast shake. OF resulted in reduced hunger and food desire while UF resulted in increased hunger and food appeal and desire. While hunger did not differ between groups, OP had higher scores for TFEQ measures (hunger, restraint and disinhibition), higher "hedonic hunger" as measured by the PFS, and greater food cravings and ratings of food appeal and desire. These results suggest that subjective hunger and desire for food change significantly after only one day of over- or underfeeding. Additionally, we found several behavioral differences between groups that are likely to promote weight gain over time in the OP.

Differences in the neuronal response to food in obesity-resistant as compared to obesity-prone individuals

Despite living in an obesogenic environment, some individuals maintain a thin phenotype compared to the majority who are at risk for weight gain and obesity. Understanding how these different phenotypes regulate energy intake is critical. The objective of this study was to examine the differences in neuronal response to visual food cues in adults recruited as either obesity-resistant (OR) or obesity-prone (OP) based on self-identification, BMI, and personal/family weight history. 25 OR and 28 OP individuals were studied after 4 days of eucaloric energy intake. Functional magnetic resonance imaging (fMRI) was performed in the fasted and acute fed states (30 min after a test meal) while subjects viewed images of foods of high hedonic value and neutral non-food objects. Measures of appetite using visual analog scales were performed before and every 30 min after the test meal for 3 h. In the fasted state, food as compared to nonfood images elicited significant response in the insula, somatosensory cortex, parietal cortex, and visual cortex in both OR and OP. The acute fed state resulted in significant attenuation of these and other brain areas in the OR but not OP individuals. Furthermore, OP as compared to OR individuals showed greater activation of medial and anterior prefrontal cortex (PFC) in response to the test meal. Adjusting for fat mass did not impact these results. Attenuation of insula/PFC response to food images in the fed state was associated with greater reductions in hunger. These findings suggest that individuals prone to weight gain and obesity have altered neuronal responses to food cues in brain regions known to be important in energy intake regulation. These altered responses may represent an important mechanism contributing to excess energy intake and risk for obesity.